Crowdshipping and Same-day Delivery: Employing In-store Customers to Deliver Online Orders
Crowdshipping and Same-day Delivery: Employing In-store Customers to Deliver Online Orders
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DOI：
10.1111/poms.13219
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发表时间：
2020-06-19
影响因子：
5
通讯作者：
Savelsbergh, Martin
中科院分区：
文献类型：
--
作者：
Dayarian, Iman;Savelsbergh, Martin
在线订单当日送达正在成为大型零售商不可或缺的服务。我们探索一种环境，让店内顾客补充公司司机并在回家的路上交付在线订单。我们考虑一个高度动态和随机的当日送货环境，其中在线订单以及愿意送货的店内顾客全天到达。研究交付能力不确定的环境是新颖且具有实际意义的。我们提出的方法很简单，但可以在短时间内产生可以在实践中使用的高质量解决方案。我们开发了两种滚动水平调度方法：一种是短视的方法，在做出决策时仅考虑系统的状态，另一种方法还结合了有关未来在线订单和店内顾客到达的概率信息。我们量化了当日送达的新型众包形式的潜在好处，并展示了利用未来概率信息的价值。我们探讨了这种众包形式的优点和缺点，并展示了环境特征变化（例如在线订单到达模式、公司车队规模和店内客户补偿）对其性能（即服务质量和运营成本）的影响。
Same-day delivery of online orders is becoming an indispensable service for large retailers. We explore an environment in which in-store customers supplement company drivers and deliver online orders on their way home. We consider a highly dynamic and stochastic same-day delivery environment in which online orders as well as in-store customers willing to make deliveries arrive throughout the day. Studying settings in which delivery capacity is uncertain is novel and practically relevant. Our proposed approaches are simple, yet produce high-quality solutions in a short amount of time that can be employed in practice. We develop two rolling horizon dispatching approaches: a myopic one that considers only the state of the system when making decisions, and one that also incorporates probabilistic information about future online order and in-store customer arrivals. We quantify the potential benefits of a novel form of crowdshipping for same-day delivery and demonstrate the value of exploiting probabilistic information about the future. We explore the advantages and disadvantages of this form of crowdshipping and show the impact of changes in environment characteristics, for example, online order arrival pattern, company fleet size, and in-store customer compensation on its performance, that is, service quality and operational cost.